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<title>The DOLPHIN Speedup-Learning System </title>

<h1>DOLPHIN</h1> <br> 


DOLPHIN is a system which combines Inductive Logic Programming
(i.e. FOIL) and Explanation-Based Learning (i.e. EBG) to learn
search-control rules for eliminating backtracking in Prolog
programs. <p>

The DOLPHIN Prolog code is available via 
<!WA0><!WA0><a href="ftp://ftp.cs.utexas.edu/pub/mooney/dolphin">anonymous ftp</a>.
See the README file here for details.

Pointers to papers on DOLPHIN can be found on our <!WA1><!WA1><a
href="http://www.cs.utexas.edu/users/ml/speedup.html">Speedup-learning</a> research page.
Below is the standard reference (click on the open book image). <p>

<! ===========================================================================>

<a name="dolphin-ijcai-93.ps.Z" </a>

<b> <li> Combining FOIL and EBG to Speed-Up Logic Programs </b> <br> 

John M. Zelle and Raymond J. Mooney <br> 

<cite> Proceedings of the Thirteenth International Joint Conference on Artificial
Intelligence</cite>, pp. 1106-111, Chambery, France, 1993. (IJCAI-93) <p>

<blockquote>
This paper presents an algorithm that combines traditional EBL
techniques and recent developments in inductive logic programming to
learn effective clause selection rules for Prolog programs.  When
these control rules are incorporated into the original program,
significant speed-up may be achieved.  The algorithm is shown to be an
improvement over competing EBL approaches in several domains.
Additionally, the algorithm is capable of automatically transforming
some intractable algorithms into ones that run in polynomial time.
</blockquote>

<!WA2><!WA2><a href="file://ftp.cs.utexas.edu/pub/mooney/papers/dolphin-ijcai-93.ps.Z">
<!WA3><!WA3><img align=top src="http://www.cs.utexas.edu/users/ml/paper.xbm"></a><p>


<hr>
<address><!WA4><!WA4><a href="http://www.cs.utexas.edu/users/estlin/">estlin@cs.utexas.edu</a></address>
